Selection methods and diversity preservation in many-objective evolutionary algorithms
Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2018)
Selection methods and diversity preservation in many-objective evolutionary algorithms. Data Technologies and Applications, https://doi.org/10.1108/dta-01-2018-0009
Purpose – One of the main components of multi-objective, and therefore, many-objective evolutionary algorithms is the selection mechanism. It is responsible for performing two...
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems
Conference Proceeding
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016)
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. In 2016 IEEE Congress on Evolutionary Computation (CEC)https://doi.org/10.1109/CEC.2016.7743969
In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control sche...
A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation
Journal Article
Segredo, E., Segura, C., León, C., & Hart, E. (2015)
A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation. Soft Computing, 19(10), 2927-2945. https://doi.org/10.1007/s00500-014-1454-y
In recent years, Multi-Objective Evolutionary Algorithms (MOEAS) that consider diversity as an objective have been used to tackle single-objective optimisation prob- lems. The...
Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016)
Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016 (296-305). https://doi.org/10.1007/978-3-319-50349-3_25
Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorithm Selection Problem was first posed. Here we propose a hyper-heuristic whic...
A novel similarity-based mutant vector generation strategy for differential evolution
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018)
A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018https://doi.org/10.1145/3205455.3205628
The mutant vector generation strategy is an essential component of Differential Evolution (DE), introduced to promote diversity, resulting in exploration of novel areas of the...
Analysing the performance of migrating birds optimisation approaches for large scale continuous problems
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016)
Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Parallel Problem Solving from Nature – PPSN XIV. , (134-144). https://doi.org/10.1007/978-3-319-45823-6_13
We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds...
Impact of selection methods on the diversity of many-objective Pareto set approximations
Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2017)
Impact of selection methods on the diversity of many-objective Pareto set approximations. Procedia Computer Science, 112, (844-853). ISSN 1877-0509
Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultane...
On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems
Journal Article
Voß, S., Segredo, E., Lalla-Ruiz, E., Hart, E., & Voss, S. (2018)
On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems. Expert Systems with Applications, 102, 126-142. https://doi.org/10.1016/j.eswa.2018.02.024
Migrating Birds Optimisation (mbo) is a nature-inspired approach which has been shown to be very effective when solving a variety of combinatorial optimisation problems. More ...
Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains
Journal Article
Marrero, A., Segredo, E., Leon, C., & Hart, E. (in press)
Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains. Evolutionary Computation,
Gathering sufficient instance data to either train algorithm-selection models or understand algorithm footprints within an instance space can be challenging. We propose an app...
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (in press)
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. In Genetic and Evolutionary Computation Conference (GECCO ’24), July 14–18, 2024, Melbourne, VIC, Australia. https://doi.org/10.1145/3638529.3654028
The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train mach...